diff --git a/rl_coach/memories/non_episodic/distributed_experience_replay.py b/rl_coach/memories/non_episodic/distributed_experience_replay.py
index c5c928b..d6bdf9c 100644
--- a/rl_coach/memories/non_episodic/distributed_experience_replay.py
+++ b/rl_coach/memories/non_episodic/distributed_experience_replay.py
@@ -51,7 +51,6 @@ class DistributedExperienceReplay(Memory):
         super().__init__(max_size)
         if max_size[0] != MemoryGranularity.Transitions:
             raise ValueError("Experience replay size can only be configured in terms of transitions")
-        # self.transitions = []
         self.allow_duplicates_in_batch_sampling = allow_duplicates_in_batch_sampling
 
         self.db = db
@@ -67,10 +66,8 @@ class DistributedExperienceReplay(Memory):
         """
         Get the number of transitions in the ER
         """
-        # Replace with distributed store len
         return self.redis_connection.info(section='keyspace')['db{}'.format(self.db)]['keys']
-        # return len(self.transitions)
-
+        
     def sample(self, size: int) -> List[Transition]:
         """
         Sample a batch of transitions form the replay buffer. If the requested size is larger than the number
@@ -84,8 +81,6 @@ class DistributedExperienceReplay(Memory):
             while len(transition_idx) != size:
                 key = self.redis_connection.randomkey()
                 transition_idx[key] = pickle.loads(self.redis_connection.get(key))
-            # transition_idx = np.random.randint(self.num_transitions(), size=size)
-
         else:
             if self.num_transitions() >= size:
                 while len(transition_idx) != size:
@@ -93,12 +88,10 @@ class DistributedExperienceReplay(Memory):
                     if key in transition_idx:
                         continue
                     transition_idx[key] = pickle.loads(self.redis_connection.get(key))
-                # transition_idx = np.random.choice(self.num_transitions(), size=size, replace=False)
             else:
                 raise ValueError("The replay buffer cannot be sampled since there are not enough transitions yet. "
                                  "There are currently {} transitions".format(self.num_transitions()))
 
-        # Replace with distributed store
         batch = transition_idx.values()
 
         return batch
@@ -125,10 +118,7 @@ class DistributedExperienceReplay(Memory):
                      locks and then calls store with lock = True
         :return: None
         """
-        # Replace with distributed store
-
         self.redis_connection.set(uuid.uuid4(), pickle.dumps(transition))
-        # self.transitions.append(transition)
         self._enforce_max_length()
 
     def get_transition(self, transition_index: int, lock: bool=True) -> Union[None, Transition]:
@@ -138,8 +128,6 @@ class DistributedExperienceReplay(Memory):
         :param lock: use write locking if this is a shared memory
         :return: the corresponding transition
         """
-        # Replace with distributed store
-        import pytest; pytest.set_trace()
         return pickle.loads(self.redis_connection.get(transition_index))
         
     def remove_transition(self, transition_index: int, lock: bool=True) -> None:
@@ -151,8 +139,6 @@ class DistributedExperienceReplay(Memory):
         :param transition_index: the index of the transition to remove
         :return: None
         """
-        # Replace with distributed store
-        import pytest; pytest.set_trace()
         self.redis_connection.delete(transition_index)
         
     # for API compatibility
@@ -162,8 +148,6 @@ class DistributedExperienceReplay(Memory):
         :param transition_index: the index of the transition to return
         :return: the corresponding transition
         """
-        # Replace with distributed store
-        import pytest; pytest.set_trace()
         return self.get_transition(transition_index, lock)
 
     # for API compatibility
@@ -173,8 +157,6 @@ class DistributedExperienceReplay(Memory):
         :param transition_index: the index of the transition to remove
         :return: None
         """
-        # Replace with distributed store
-        import pytest; pytest.set_trace()
         self.remove_transition(transition_index, lock)
 
     def clean(self, lock: bool=True) -> None:
@@ -182,7 +164,6 @@ class DistributedExperienceReplay(Memory):
         Clean the memory by removing all the episodes
         :return: None
         """
-        import pytest; pytest.set_trace()
         self.redis_connection.flushall()
         # self.transitions = []
 
@@ -191,9 +172,6 @@ class DistributedExperienceReplay(Memory):
         Get the mean reward in the replay buffer
         :return: the mean reward
         """
-        # Replace with distributed store
-        import pytest; pytest.set_trace()
         mean = np.mean([pickle.loads(self.redis_connection.get(key)).reward for key in self.redis_connection.keys()])
-        # mean = np.mean([transition.reward for transition in self.transitions])
-
+        
         return mean